Data incorporating large quantities of variables is becoming increasingly commonplace, especially in data sets that are sufficiently large that they may be generated and/or stored by multiple computing devices. In addition to the challenges of handling such a large quantity of data, increasing the quantity of variables in a data set by even a small degree tends to add to at least the complexity of relationships among the data values, and may result in an increase in data size. Among such challenging data sets are large random samples generated by various forms of statistical analysis. Examples include large simulated samples randomly generated from a posterior probability distribution derived by the performance of a Bayesian analysis on a prior probability distribution, a model and/or various parameters.